Abdulrahman Mohamed

Key Skills

Software

Axiom AI

Clickworker

CrowdFlower

Data Annotation Tech

Figure Eight

Google Cloud Vertex AI

Labelbox

LabelImg

Label Studio

Mighty AI

Redbrick AI

Remotasks

Snorkel AI

Surge AI

V7 Labs

Other

Internal/Proprietary Tooling

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Label Types

Action Recognition

Audio Recording

Data Collection

Prompt Response Writing SFT

Text Generation

Freelancer Overview

I am an experienced data annotator and transcription specialist with a strong background in conversational and audio data. I have worked on multiple projects involving Arabic transcription, labeling of chatbot interactions, and structured dataset creation for AI training. My attention to detail ensures high-quality, accurate data that meets project requirements. I am skilled in text and audio annotation, NLP data labeling, and evaluating AI-generated content for tone, completeness, and accuracy. Familiarity with structured data formats and basic SQL literacy allows me to validate function calls and ensure safe and reliable dataset preparation. I am motivated, proactive, and eager to contribute to AI training projects across diverse industries.

Labeling Experience

Video & Image Annotation for AI Training

Label StudioImageBounding BoxPolygon

Worked on annotation projects involving images and videos for AI model training. Tasks included labeling objects, buttons, and human actions using bounding boxes and polygons, as well as action recognition in sports (e.g., volleyball: spike, block, serve, set, receive) and food domain videos (e.g., chopping, stirring, plating). Ensured high accuracy and consistency by following strict project guidelines, performing self-review, and incorporating QA feedback. Annotated datasets ranged from 50–100 images/videos for practice, with plans to scale up for larger production datasets.

Worked on annotation projects involving images and videos for AI model training. Tasks included labeling objects, buttons, and human actions using bounding boxes and polygons, as well as action recognition in sports (e.g., volleyball: spike, block, serve, set, receive) and food domain videos (e.g., chopping, stirring, plating). Ensured high accuracy and consistency by following strict project guidelines, performing self-review, and incorporating QA feedback. Annotated datasets ranged from 50–100 images/videos for practice, with plans to scale up for larger production datasets.

2025 - 2025

audio Annotation for Persons

Data Annotation TechAudioPolygonSegmentation

Worked on an audio recording project where I recorded clear, high-quality voice samples following specific scripts and pronunciation guidelines. Ensured consistency in tone, pace, and clarity across all recordings. Maintained attention to detail and adhered strictly to project instructions to meet quality standards. Collected and submitted recordings for a practice dataset, gaining hands-on experience in audio data collection for AI training.

Worked on an audio recording project where I recorded clear, high-quality voice samples following specific scripts and pronunciation guidelines. Ensured consistency in tone, pace, and clarity across all recordings. Maintained attention to detail and adhered strictly to project instructions to meet quality standards. Collected and submitted recordings for a practice dataset, gaining hands-on experience in audio data collection for AI training.

2024 - 2024

Education

Work History